[PDF][PDF] Computer Vision and Deep Learning-enabled Weed Detection Model for Precision Agriculture.

R Punithavathi, ADC Rani, KR Sughashini… - Comput. Syst. Sci …, 2023 - researchgate.net
Presently, precision agriculture processes like plant disease, crop yield prediction, species
recognition, weed detection, and irrigation can be accomplished by the use of computer …

Computer vision based robotic weed control system for precision agriculture

MP Arakeri, BPV Kumar, S Barsaiya… - … on Advances in …, 2017 - ieeexplore.ieee.org
India is primarily an agriculture-based country and its economy largely depends upon the
agriculture. But, most of the crops grown by the farmer are affected by weeds. Weed …

[HTML][HTML] Weed detection in canola fields using maximum likelihood classification and deep convolutional neural network

MH Asad, A Bais - Information Processing in Agriculture, 2020 - Elsevier
Herbicide use is rising globally to enhance food production, causing harm to environment
and the ecosystem. Precision agriculture suggests variable-rate herbicide application based …

Low-cost weed identification system using drones

WC Liang, YJ Yang, CM Chao - 2019 Seventh International …, 2019 - ieeexplore.ieee.org
Weeds compete with crops for resources such as light, nutrients, water and space. When
mature, weeds can produce thousands to hundreds of thousands of seeds that can survive …

Performance of deep learning models for classifying and detecting common weeds in corn and soybean production systems

A Ahmad, D Saraswat, V Aggarwal, A Etienne… - … and Electronics in …, 2021 - Elsevier
Knowing precise location and having accurate information about weed species is a
prerequisite for developing an effective site-specific weed management (SSWM) system …

Weed detection by faster RCNN model: An enhanced anchor box approach

MH Saleem, J Potgieter, KM Arif - Agronomy, 2022 - mdpi.com
To apply weed control treatments effectively, the weeds must be accurately detected. Deep
learning (DL) has been quite successful in performing the weed identification task. However …

[HTML][HTML] Deep learning-based early weed segmentation using motion blurred UAV images of sorghum fields

N Genze, R Ajekwe, Z Güreli, F Haselbeck… - … and Electronics in …, 2022 - Elsevier
Weeds are undesired plants in agricultural fields that affect crop yield and quality by
competing for nutrients, water, sunlight and space. For centuries, farmers have used several …

Multi-modal and multi-view image dataset for weeds detection in wheat field

K Xu, Z Jiang, Q Liu, Q Xie, Y Zhu, W Cao… - Frontiers in Plant …, 2022 - frontiersin.org
Weeds in wheat fields compete with wheat for light, water, fertilizer, and growth space, and
therefore are one of the main biohazards that limit the yield and quality formation of wheat …

Real-time crop recognition in transplanted fields with prominent weed growth: a visual-attention-based approach

N Li, X Zhang, C Zhang, H Guo, Z Sun, X Wu - IEEE Access, 2019 - ieeexplore.ieee.org
Crop recognition is one of the key processes for robotic weeding in precision agriculture,
which remains an open problem due to the unstructured field environment and the wide …

A detailed review on challenges and imperatives of various cnn algorithms in weed detection

S Veeragandham, H Santhi - 2021 International conference on …, 2021 - ieeexplore.ieee.org
Weed is one of the main reason for getting less production in agriculture field. At present,
farmers are using herbicides to control the weed but it's having negative impact on crop …